Groundwater in Mediterranean regions faces increasing stress from climate change and agricultural pressures, requiring robust tools to assess future vulnerability. This study evaluates the vulnerability of Almyros aquifer, Thessaly, Greece, to nitrate pollution using the DRASTIC index under the high-emission scenario RCP8.5. Bias-corrected rainfall and temperature from a best-fit Med-CORDEX model were used in an Integrated Modeling System (IMS) combining UTHBAL, MODFLOW, and MT3DMS to simulate recharge, water table, and nitrate fluxes under climate forcing. These outputs informed DRASTIC calculations for the baseline period 1991–2018, using observed and integrated simulation results, allowing validation against observations. DRASTIC was applied to two future horizons 2031–2060 and 2071–2100, using IMS results under climate change, to assess the future nitrate vulnerability of the aquifer. Spatial patterns of vulnerability were consistent across periods: high vulnerability dominated the northeastern, eastern, southern, and southeastern zones, medium in central area, and low in west. The DRASTIC results for the baseline period (1991-2018) using the observed and simulated timeseries of input data showed minor differences, with low and medium classes slightly higher in simulation, and high classes differed by 3%. Pearson correlations with normalized NO₃^- (0.70 and 0.67, respectively) confirmed robust DRASTIC performance, particularly in high-vulnerability zones, highlighting areas where monitoring and management should be prioritized. Aggregating classes into low to very-low, medium, and high to very-high revealed temporal shifts. During the baseline period, low to very-low vulnerability dominated (42.0%), followed by medium (25.8%) and high to very-high (32.1%). By mid-century (2031–2060), high vulnerability increased to 35.6%, while low remained stable (42.4%) and medium decreased (22.0%). By-late century (2071–2100), medium vulnerability expanded (37.5%), surpassing low(34.1%) and approaching high (28.4%). These shifts were pronounced in low-lying agricultural/coastal areas, reflecting spatially differentiated impacts of climate-driven changes in recharge and water depth. These findings demonstrate that integrating bias-corrected climate projections with hydrological modeling provides realistic vulnerability assessments and identifies spatial hotspots for adaptive groundwater management.